In this paper, we introduce an innovative way to
model and predict high-definition (HD) video traces encoded
with H.264/AVC encoding standard. Our results are based on
comparing over 50 HD video traces. We show through our
results that our model: simplified seasonal ARIMA (SAM)
provides a good representation for HD videos, and it provides
significant improvements in prediction accuracy over other
regressions methods. In addition, we discuss our methodology
to collect and encode our library of HD video traces. We
describe the tools that we have created and used in generating
create and analyzing these traces. We have made these tools,
along with our large collection of HD video traces, available for
the research community. We illustrate the simplicity of our
approach and we discuss the importance of our modeling and
prediction method and its impact on other areas of study.